## The proposed role of scoring systems

The proposed role of scoring systems has been based on the quantification of case mix and the development of mathematical equations to estimate probabilities of outcome for intensive care patients. Outcome has usually been measured as death before discharge from hospital following intensive care.

Each scoring system describes the association between independent variables (case mix) and the dependent variable (death before discharge from hospital following intensive care) in the form of a mathematical equation known as a multiple logistic regression equation. APACHE II, APACHE III, and SAPS II sum the weights for some or all of the independent variables into a score before incorporation into the mathematical equation. The mathematical equation describes the strength of the association of each of the different independent variables with the dependent variable, while allowing for the effect of all the other independent variables in the same equation.

The mathematical equation for each scoring system can be applied to a group of intensive care patients, for whom data are available on the independent variables, to estimate the expected hospital death rate. On applying the equation, the probability of death before discharge from hospital following intensive care can be estimated for each patient and summed for all the patients to yield the expected hospital death rate for the whole group of patients. The expected hospital death rate can then be compared with the actual hospital death rate. This is often displayed in the form of a ratio of actual to expected hospital death rates, referred to as the standardized mortality ratio (SMR). Confidence intervals can be calculated to determine whether the value of the SMR is statistically significantly different from 1.0, the value obtained when the expected and actual hospital death rates are the same (Rapoportetai: 1994).

Given the above, the proposed roles of scoring systems in intensive care can be divided into three main areas: comparative audit, evaluative research, and the clinical management of individual patients.

### Comparative audit

Comparing the actual outcomes with the expected outcomes for groups of patients, calculated using a scoring system, has been proposed as the basis for initial exploratory control comparisons of different providers. The use of case-mix-adjusted outcomes as a measure of the clinical effectiveness of intensive care assumes that an sMr greater than 1.0 may reflect poor care and, conversely, an SMR less than 1.0 may reflect good care.

Local clinical audit could then be implemented to investigate the reasons for any unexpected results. For example, it may be that a high SMR arose because of poor outcomes in one particular group of patients, such as respiratory cases, or at a particular time, such as at night.

### Evaluative research

As described above, it is not always possible to evaluate interventions using randomized study designs. When non-randomized or observational methods are used, a valid means of adjusting for case-mix differences between groups of patients is needed. Accurate objective estimates of the probabilities of hospital death, when translated into expected hospital death rates for groups of patients, have been proposed as the basis for research studies to identify those components of intensive care structure and process that are linked to improved patient outcome.

Scoring systems have also been proposed to aid stratification in randomized controlled trials. All interventions used in intensive care should be subject to a randomized controlled trial to demonstrate clinical effectiveness. Given the considerable heterogeneity of the intensive care patient population, it is proposed that stratification using an accurate objective estimate of the risk of hospital death might create a more homogeneous subset of patients to isolate better the effects of the intervention on the outcome.

### Clinical management of individual patients

For their simplest use in the clinical management of individual patients, scores from scoring systems have been proposed as a form of clinical shorthand, i.e. a common standard terminology to convey information rapidly about a patient. They have also been proposed for use in triage to classify patients according to severity of illness.

Although the early scoring systems were proposed only as a means for comparing observed and expected outcomes for groups of intensive care patients, some of the subsequent second- and third-generation methods are promoted as methods to guide the clinical care of individual patients. It is proposed that an accurate objective estimate of the risk of hospital death can provide additional information to help make clinical decisions about treatment aims for individual patients. Such decisions might include when to withdraw treatment or when to discharge a patient.

Some of the recent methods have incorporated trend analysis, i.e. the concept of modeling probabilities of outcome over time, into their development in an attempt to improve the ability to predict outcome for individual intensive care patients.

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